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arxiv: 2604.21878 · v1 · submitted 2026-04-23 · 💻 cs.HC

Recognition: unknown

Gradual Voluntary Participation: A Framework for Participatory AI Governance in Journalism

Matilde Barbini , Stefano Sorrentino , Daniel Gatica-Perez
Authors on Pith no claims yet

Pith reviewed 2026-05-09 20:55 UTC · model grok-4.3

classification 💻 cs.HC
keywords participatory AIAI governancejournalismparticipatory designgradual participationworkplace AIperception gapepistemic burdens
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The pith

Journalists trust AI tools more when they perceive they can gradually and voluntarily influence how those tools are used in the newsroom.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Interviews with ten journalists revealed a perception gap: trust in AI depends on how much agency people feel they have within workplace participatory processes. Traditional participatory design struggles with AI because systems are opaque and hard to influence, leading to epistemic burdens and superficial consultations. The paper proposes the Gradual Voluntary Participation framework with five core principles that treat participation as an ongoing, optional process rather than fixed workshops. This framework uses a two-dimensional matrix of depth and scope instead of ladder models to map stakeholders and support local governance. If correct, it would let newsrooms operationalize participation in ways that build legitimacy and ownership during AI integration.

Core claim

Through interviews with 10 journalists, the paper identifies a perception gap showing that trust in AI depends on perceived agency within workplace participatory workflows. Informed by these findings, it introduces the Gradual Voluntary Participation (GVP) framework and its five core principles, reconceptualizing participation as a gradual and voluntary process that can be operationalized at the newsroom level beyond fixed workshops or one-time preference-elicitation campaigns. The framework addresses epistemic burdens, participatory ceilings, and performative consultations by treating gradualism and voluntariness as design dimensions that shape perception, legitimacy, and ownership, and by,

What carries the argument

The Gradual Voluntary Participation (GVP) framework, which maps stakeholders on a bidimensional matrix of participation depth and scope while treating gradualism and voluntariness as adjustable design dimensions to build agency and legitimacy.

If this is right

  • Participation becomes a continuous, optional process rather than one-time events, allowing operationalization directly in newsrooms.
  • The bidimensional matrix replaces unidimensional ladders to better capture varying depths and scopes of stakeholder involvement.
  • Gradualism and voluntariness function as design dimensions that directly affect perceptions of legitimacy and ownership.
  • The approach balances technological transformation with empowerment by addressing performative consultations and participatory ceilings.
  • Local participatory AI governance becomes feasible in hybrid workplaces without requiring full stakeholder control over opaque systems.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The framework could be adapted and tested in other high-stakes professional settings where AI is introduced into expert workflows.
  • Implementing the matrix structure might surface new practical challenges around measuring and adjusting participation depth over time.
  • If the perception gap closes under GVP, newsrooms might see faster and more sustained adoption of AI tools with less internal resistance.

Load-bearing premise

That insights from interviews with a small sample of ten journalists are sufficient to identify generalizable issues like epistemic burdens and participatory ceilings and to develop a framework that can be operationalized across diverse newsroom settings.

What would settle it

A follow-up study that applies the GVP principles in multiple real newsrooms and measures whether journalists report higher perceived agency, lower epistemic burdens, and increased trust in AI compared to standard participatory approaches.

Figures

Figures reproduced from arXiv: 2604.21878 by Daniel Gatica-Perez, Matilde Barbini, Stefano Sorrentino.

Figure 1
Figure 1. Figure 1: Overview of paper contributions and their relationships. The three contributions build sequentially: empirical findings from [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The GVP checkerboard, where each quadrant represents a distinct degree of participation across various scopes and depths of [PITH_FULL_IMAGE:figures/full_fig_p017_2.png] view at source ↗
read the original abstract

The integration of AI into journalism challenges participatory design (PD), particularly with respect to stakeholder influence, workplace perceptions, and organizational dynamics. Traditional PD assumes that users can shape technologies, yet AI systems resist influence due to opaque data, fixed architectures, and inaccessible objectives. Through interviews with 10 journalists, we identify the perception gap, showing that trust in AI depends on perceived agency within workplace participatory workflows. Informed by these findings, we introduce the Gradual Voluntary Participation (GVP) framework in journalism and its five core principles, reconceptualizing participation as a gradual and voluntary process that can be operationalized at the newsroom level, beyond fixed workshops or one-time preference-elicitation campaigns. Addressing epistemic burdens, participatory ceilings, and performative consultations, GVP treats gradualism and voluntariness as design dimensions that shape perception, legitimacy, and ownership. Moving beyond unidimensional ladder metaphors and adopting a bidimensional matrix structure, the framework maps stakeholders across depth and scope, offering a new model for local participatory AI governance that balances technological transformation with stakeholder empowerment in rapidly evolving hybrid workplaces.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper claims that interviews with 10 journalists reveal a perception gap in which trust in AI depends on perceived agency within workplace participatory workflows. Informed by these findings, it introduces the Gradual Voluntary Participation (GVP) framework and its five core principles, which reconceptualize participation as a gradual and voluntary process operationalizable at the newsroom level via a bidimensional matrix that maps stakeholders along depth and scope dimensions, addressing epistemic burdens, participatory ceilings, and performative consultations beyond traditional PD approaches.

Significance. If the framework's generalizability holds, it would offer a practical, bidimensional alternative to unidimensional ladder models of participation, enabling newsrooms to design AI governance processes that better balance technological opacity with stakeholder empowerment and ownership. The qualitative identification of the perception gap and the emphasis on gradualism/voluntariness as design dimensions could inform empirical studies and local implementations in hybrid journalism workplaces.

major comments (2)
  1. [Methods] Methods section: No details are provided on the interview protocol, sampling strategy (e.g., selection criteria, diversity across newsroom size, ownership, or AI maturity), data analysis approach, or saturation criteria. This directly affects the central claim that the perception gap and five GVP principles were identified from the interviews and can be generalized to operationalize participation across diverse newsroom settings.
  2. [Findings and Framework] Findings and Framework sections: The derivation of the five core principles and the bidimensional matrix from the n=10 sample is presented without discussion of limitations, variation in participant experiences, or evidence that the insights address performative consultations beyond the specific cases studied. This load-bearing step for the framework's claimed utility requires stronger justification or additional data.
minor comments (2)
  1. [Abstract] Abstract: The claim that GVP 'can be operationalized at the newsroom level' would benefit from a brief example of how the matrix applies to a concrete AI tool (e.g., content recommendation system) to clarify the transition from principles to practice.
  2. [Related Work] The manuscript would be strengthened by explicit comparison of the GVP matrix to existing PD frameworks (e.g., Arnstein's ladder or later HCI adaptations) in a dedicated related-work subsection.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We are grateful to the referee for the constructive and detailed feedback, which identifies key areas where the manuscript can be strengthened. We address the major comments point by point below and will revise the paper accordingly to improve methodological transparency and the grounding of the GVP framework.

read point-by-point responses

  1. Referee: [Methods] Methods section: No details are provided on the interview protocol, sampling strategy (e.g., selection criteria, diversity across newsroom size, ownership, or AI maturity), data analysis approach, or saturation criteria. This directly affects the central claim that the perception gap and five GVP principles were identified from the interviews and can be generalized to operationalize participation across diverse newsroom settings.

    Authors: We agree that the current Methods section lacks necessary detail, which limits the ability to evaluate the robustness of the findings. In the revised manuscript, we will expand the Methods section to provide a complete account of the semi-structured interview protocol (including key questions), the purposive sampling strategy with explicit selection criteria and efforts to capture diversity in newsroom size, ownership, and AI maturity, the thematic analysis process, and the criteria used to determine saturation. These additions will directly support the claims regarding the perception gap and GVP principles while clarifying the exploratory scope of the study. revision: yes

  2. Referee: [Findings and Framework] Findings and Framework sections: The derivation of the five core principles and the bidimensional matrix from the n=10 sample is presented without discussion of limitations, variation in participant experiences, or evidence that the insights address performative consultations beyond the specific cases studied. This load-bearing step for the framework's claimed utility requires stronger justification or additional data.

    Authors: We acknowledge that the manuscript would be improved by explicitly addressing limitations and variations in the derivation of the principles and matrix. In the revision, we will add a dedicated discussion subsection that covers the constraints of the n=10 sample, observed variations in participant experiences (e.g., differences tied to newsroom context or AI exposure), and specific evidence from the interviews on how the framework targets performative consultations. We will clarify that the GVP framework is a conceptual model informed by the qualitative data rather than a direct empirical generalization, and we will note the need for future validation studies. This provides stronger justification for the framework's utility at the newsroom level. revision: yes

Circularity Check

0 steps flagged

No circularity: GVP framework derived from independent interview data without self-referential reduction

full rationale

The paper's derivation chain proceeds from qualitative interviews with 10 journalists to identification of a perception gap, then to introduction of the GVP framework and its five principles as informed by those findings. No equations, fitted parameters, or self-citations are present in the provided text. The framework is not defined in terms of itself, nor are any 'predictions' or principles shown to reduce by construction to the interview inputs. This is a standard empirical-to-conceptual move in participatory design research and remains self-contained; generalizability concerns are evidentiary rather than circular.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 1 invented entities

The paper's contribution is a conceptual framework derived from qualitative interviews. No numerical free parameters are present. The main assumption is that small-sample interview insights can support a generalizable governance model for AI in newsrooms.

axioms (1)
  • domain assumption Participatory design approaches can be meaningfully adapted to opaque AI systems in journalism despite fixed architectures and inaccessible objectives.
    The abstract notes that traditional PD assumes users can shape technologies but AI resists influence, yet proceeds to build a PD-based framework.
invented entities (1)
  • Gradual Voluntary Participation (GVP) framework no independent evidence
    purpose: To provide a bidimensional model for local participatory AI governance that balances technological transformation with stakeholder empowerment.
    New framework introduced based on interview findings to address specific challenges like perception gap and performative consultations.

pith-pipeline@v0.9.0 · 5492 in / 1467 out tokens · 45653 ms · 2026-05-09T20:55:46.112754+00:00 · methodology

discussion (0)

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Reference graph

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